Optical coherence elastography (OCE) provides mechanical contrast on the micro-scale and has shown promise in a number of clinical applications. In the majority of OCE methods, local homogeneity is inherently assumed in the mechanical models, which results in low accuracy in complex tissues. Here, we present a novel compression OCE method that exploits tissue heterogeneity to generate mechanical contrast in human breast tissue by mapping the full strain tensor. We used the strain tensor to map mechanical parameters such as Euler angle of principal compression. We also demonstrate a new form of quantitative OCE by mapping local Poisson’s ratio.
Solid tumours are typically first diagnosed by palpation, revealing increased stiffness, while cancer cells are usually reported to be softer. The mechanical characteristics are not universal and depend on the cell type and the stage of development. Current techniques are usually point or 2D measurement techniques that lack depth penetration in 3D samples. We are developing optical coherence mechano-microscopy integrated with a confocal fluorescence microscope as a platform to investigate the mechanical phenotypes of 3D cancer models, mimicking the conditions in the native tumour microenvironment. This platform enables unique measurement of the 3D elasticity (i.e. Young’s modulus) of metastatic and non-metastatic breast cancer cell spheroids embedded in GelMAl, presenting the extracellular matrix, co-registered with fluorescence images. Our findings show that cells at the centre of non-metastatic cancer cell spheroids are softer (5.8 kPa) than the cells at the periphery (12.7 kPa). In contrast, migrating cells at the periphery of the metastatic cancer cell spheroids are softer (5.7 kPa) than the less motile cells at the centre of these spheroids (8.0 kPa).
Strain retrieval from maps of displacement due to mechanical loading is central to optical coherence elastography. However, displacement data is usually highly oscillatory since it is derived from the phase difference between OCT images. Oscillations limit sensitivity and signal to noise ratio of retrieved strain. We present a novel strain retrieval method which determines the unique spectral domain transformation and transverse displacement compensation that maps the unloaded A-scan to the loaded A-scan, exactly, for regions of constant strain. Our novel method of strain retrieval has a higher sensitivity and signal to noise ratio than existing approaches.
Multicellular tumour spheroids have recently become important tools to investigate different stages of cancer development due to their 3D nature. We propose dynamic optical coherence microscopy (OCM) as a label-free low coherence interferometric technique for 3D characterization of morphology and cell motility during cell migration in multicellular cancer cell spheroids. We integrate dynamic OCM with confocal fluorescence microscopy (CFM) to validate and co-register the subcellular-scale endogenous contrast generated by dynamic OCM signal with sub-cellular features such as cell nucleus and membrane. We apply dynamic OCM integrated with CFM to scan metastatic and non-metastatic breast cancer cell spheroids embedded in gelatin-methacryloyl (GelMA) hydrogel and demonstrate that dynamic OCM provides high-contrast morphological imaging equivalent to that of confocal fluorescence in cancer cell spheroids. We use dynamic OCM to visualize different phases of cell migration such as invadopodia formation, cells breaking off from the primary tumour model, and migrating cells presenting a spindle-like shape, and to characterize cell motility at different stages.
Multicellular spheroids are a powerful model to study biochemical and biophysical interactions between cancer cells during growth and progression. However, little is known about how the biomechanics of the three-dimensional (3-D) microenvironment control cancer cell behaviors due to the lack of enabling technologies that can measure 3-D subcellular-scale elasticity and co-register it with the morphology and function of cells in a 3-D microenvironment. Here, we propose a multimodal imaging system that integrates an optical coherence microscopy-based subcellular mechano-microscopy system with a multi-channel confocal fluorescence microscopy system. Using this multimodal imaging system, we scan non-metastatic MCF7 breast cancer cell spheroids encapsulated in gelatin methacryloyl (GelMA) hydrogels and co-register 3-D intra-spheroid elasticity with subcellular structures, such as nuclei and cell membranes.
Compression optical coherence elastography depends heavily on strain retrieval from maps of displacement due to mechanical loading. Displacement data is derived from the phase difference between OCT images and is highly oscillatory due to speckle. This limits strain sensitivity and signal to noise ratio. We present an alternative approach to strain retrieval that overcomes this speckle induced limitation by determining the unique spectral domain transformation that maps unloaded A-scans to the loaded A-scans, exactly, for regions of constant strain. Our novel method of strain retrieval has a higher sensitivity and signal to noise ratio than existing approaches.
Tissue function is dependent on its mechanical properties. Characterizing the mechanical properties of tissue on the micro-scale will enable an improved understanding of its physiological function and aid to identify disease at an early stage. In this study, we present a tension-based optical coherence elastography that maps the micro-scale strain tensor resulting from tensile loading to study the mechanics of load-bearing tissues (e.g., tendon) that routinely resist tensile loading. We demonstrate this technique through experiments of phantom and tendon tissue, presenting the micro-scale mechanical contrast arising from the local structural and mechanical heterogeneity of samples under tensile loading.
Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique that visualizes micro-scale tissue stiffness. Current benchtop QME shows great potential for identifying cancer in excised breast tissue (96% diagnostic accuracy), but cannot image cancer directly in the patients. We present the development of a handheld QME probe to directly image the surgical cavity in vivo during breast-conserving surgery (BCS) and a preliminary clinical demonstration. The results from 21 patients indicate that in vivo QME can identify residual cancer based on the elevated stiffness by directly imaging the surgical cavity, potentially contributing to a more complete cancer excision during BCS.
Strain retrieval from maps of displacement due to mechanical loading is central to optical coherence elsatography. However, displacement data is usually highly oscillatory since it is derived from the phase difference between OCT images. Oscillations limit sensitivity and signal to noise ratio of retrieved strain. We present an alternative approach to strain retrieval that does not use phase difference, but determines the unique spectral domain transformation that maps the unloaded A-scan to the loaded A-scan, exactly, for regions of constant strain. Our novel method of strain retrieval has a higher sensitivity and signal to noise ratio than existing approaches.
Mechanical properties of cells and extracellular matrix play important roles in the regulation of various biological processes such as gene expression, adhesion, and migration of cells. However, it is challenging to map three-dimensional (3D) elasticity on the micro-scale using existing techniques. We propose subcellular mechano-microscopy, a variant of compression-based optical coherence elastography, for 3D elastography of cell spheroids with isotropic elasticity resolution of 10 µm, over large fields of view covering multiple spheroids. We use the proposed technique to scan multicellular non-metastatic breast cancer cell spheroids embedded in gelatin methacryloyl (GelMA) hydrogels and co-register the micro-elastograms with fluorescence microscopy images.
Re-excision following breast-conserving surgery (BCS) due to suspected residual cancer left from the primary surgery causes substantial physical, psychological, and financial burdens for patients. This study provides a first-in-human clinical study of in vivo quantitative micro-elastography (QME) for in-cavity identification of residual cancer. A custom-built handheld QME probe is used to directly scan the surgical cavity for imaging the micro-scale tissue stiffness during BCS. In vivo QME of 21 patients, validated by co-registered histopathology of the excised specimens, demonstrates the capability to detect residual cancer based on its elevated micro-scale stiffness, potentially contributing to a more complete cancer removal.
Quantitative micro-elastography (QME) maps tissue elasticity. We report the first application of QME with encapsulation technique on skeletal muscles by demonstrating the variations of elasticity between normal and dystrophic mouse muscles.
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